I am seeking a career transition award to assist my studies of immunodominance hierarchies in the influenza infection model. I have a strong background in host-pathogen interactions in parasitic and viral models from my graduate and postdoctoral work, respectively. While a significant part of my postdoctoral work has focused on CD4+ T cell activation and expansion in influenza, I have also developed several infection models for the investigation of immunodominance. The phenomenon of immunodominance has been observed in B cell, CD4+ T cell and CD8+ T cell antigen-specific responses in virtually all types of infection and in tumor immunity models. It is still uncertain why one response dominates over other responses, however it is clear that more than one parameter is responsible. In the influenza infection model in BL/6 mice we observe a striking immunodominance hierarchy. Our study arises out of a series of observations suggesting precursor frequency and epitope density are the primary determinants of CD8+ T cell immunodominance hierarchies in the influenza model. However, our inability to accurately measure these two parameters has limited our attempts to directly model how they might influence immunodominance in in vivo models. In this proposal, I seek to test a mathematical model of immunodominance I have generated as the central hypothesis. To test this hypothesis, I propose the development of more quantitatively precise techniques for measuring both epitope density and precursor frequency. Understanding immunodominance is crucial to rational vaccine design and to immunotherapy for persistent infections such as HIV, or for anti-tumor immune treatments. Currently, estimating a "good" epitope in vivo relies on empirical observation and experimentation;we have few tools for predicting epitopes that generate a response that is robust, will successfully avoid immune escape, or be protective. The mathematical models in this proposal and parameter measurements should allow a more prospective approach towards therapeutic design as well increasing our understanding of the essential structure of CD8+ T cell responses.